In general, various physiological functions are regulated by the dynamic interactions between various bioactive molecules. If such interactions do not occur properly, problems arise to cause diseases. For example, proteins in vivo perform their functions by interaction with other proteins. Generally, two proteins having complementary structures interact with each other, and a bioactive compound interacts specifically with the specific portion of the three-dimensional protein structure. Generally, the interaction between two proteins strongly implies that they are functionally related. Furthermore, a bioactive compound interacting specifically with the specific portion of a disease-associated protein has potential as a therapeutic agent which can diagnose, prevent, treat or alleviate the disease by controlling the activity of the protein.
Accordingly, in the field of new drug development, various methods for detecting novel target proteins or screening bioactive molecules as drug candidates by detecting the interaction between a “bait” whose function and feature are known and a “prey” which is an interaction partner to be analyzed and detected have been studied. Thus, the identification and isolation of a novel target protein through the analysis of the interaction between bioactive molecules are considered as very important research projects for obtaining useful information about the activity, effectiveness and adverse effects of bioactive compounds. Additionally, target proteins promote the understanding of biological pathways and signal transduction systems and provide information on fundamental cellular regulation and disease mechanisms. Such information is a very powerful tool for developing new drugs, improving existing drugs and discovering the novel pharmaceutical use of existing drugs by analyzing and detecting bioactive compounds which interact with the target proteins.
Modern medicine faces the challenge of developing safer and more effective therapies. However, many drugs currently in use are prescribed by the biological effects in disease models without their target proteins and molecular targets (L. Burdine et al., Chem. Biol. 11:593, 2004; J. Clardy et al., Nature 432:829, 2004). Bioactive natural products are an important source for drug development, but their mode of action are usually unknown (J. Clardy et al., Nature 432:829, 2004). Elucidation of their physiological targets and molecular targets is essential for understanding their therapeutic and adverse effects, thereby enabling the development of improved second-generation therapeutics. Moreover, the discovery of novel targets of clinically proven compounds may suggest new therapeutic applications (T. T. Ashburn et al., Drug Discov. 3:673, 2004).
In chemical-biological field employing high-throughput cell-based screening, “target screening” is used to identify small molecules with a desired phenotype from large compound libraries (R. L. Strausberg et al., Science 300:294, 2003; B. R. Stockwell, Nature 432:846, 2004). Despite the great benefits of such screening, this approach has been hampered by the daunting task of target identification. However, the development of such identification technology is very important in various bioscience fields, including genomics, proteomics and system biology, because effective detection of diverse intracellular molecular interactions, including protein (or small molecule)-protein, is essential for understanding dynamic biological processes and regulatory networks.
In the field of target screening, several technologies, including affinity chromatography (Phizicky, E. M. et al., Microbiol. Rev., 59:94, 1995; Mendelsohn A. R. et al., Science, 284:1948, 1999), protein-small molecule microarray, phage display (Sche, P. P. et al., Chem. Biol., 6:707, 1999), yeast two-/three-hybrid assay (Licitra, E. J. et al., Proc. Natl. Acad. Sci. USA, 93:12817, 1996), expression profiling, and parallel analysis of yeast strains with heterologous deletions (Zheng et al., Chem. Biol., 11: 609, 2004), have been used to analyze interactions between bioactive molecules. However, such technologies all suffer from diverse problems, including high background, false positives, low sensitivity, inappropriate folding after protein expression, indirectness, lack of modification after protein expression, or limited target accessibility including cellular compatibility. In addition, the use of artificial experimental milieu, such as in vitro binding conditions or non-mammalian cells, sometimes causes errors in experimental results.
Accordingly, it is most preferable to directly examine the interaction between bioactive molecules in a state in which high sensitivity and selectivity were considered in physiological or pharmaceutical terms. Technologies for probing molecular interactions within living mammalian cells such as fluorescence resonance energy transfer (FRET) (Moshinsky, D. J. et al., Screen., 8(4): 447, 2003) or protein-fragment complementation assay (PCA) are available, but they are limited by the requirements for specific spatial orientation or distance between the interaction partners.
Thus, it is considered that it is very important to develop the above-described base technology in order to offer various advantages over the prior art.
First, by probing the interactions between physiologically or pharmaceutically relevant bioactive substances or molecules, misleading outcomes produced by an artificial experimental setting can be greatly diminished. Second, it is possible to directly translate the interaction between bioactive molecules into a clear readout signal, unlike indirect readout methods that are dependent on overall expression profiles or complex biological phenotypes. Thus, intrinsic false positives/negatives or error-prone deductions about bioactive molecules and molecular targets can be obviated. Third, it is possible to perform dynamic, single-cell analysis for the interactions between bioactive molecules. Dynamic analysis of individual living cells provides an effective method which can analyze intracellular processes occurring non-simultaneously among heterogeneous cells, over a broad range in physiological and pharmaceutical terms.
Therefore, the above-described base technology can be used to detect a variety of biological interactions (e.g., interaction between a bioactive small molecule and a protein) and protein modifications (e.g., phosphorylation) within living cells in a broad range of tissues and disease states.
In order to satisfy the requirements of the above-described base technology and solve the problems occurring in the prior art, the present inventors have studied a method for dynamically analyzing the interactions between bioactive molecules not only in vitro, but also in vivo. As a result, the present inventors have found that the interactions between bioactive molecules can be analyzed and detected by analyzing whether the interactions between various bioactive molecules result in the formation of a nano-assembly matrix or the bioactive molecules co-locate on the nano-assembly matrix, thereby completing the present invention.